Best Oracle 1z0-1096-23 2024 Training With 73 QA's [Q36-Q58]

Best Oracle 1z0-1096-23 2024 Training With 73 QA’s [Q36-Q58]

1. Januar 2024 admin 0 Kommentare

5/5 - (1 Abstimmung)

Best Oracle 1z0-1096-23 2024 Training With 73 QA’s

Oracle 1z0-1096-23 Certification Exam Questions

Oracle 1z0-1096-23 Exam Syllabus Topics:

Thema	Einzelheiten
Thema 1	Working with Jobs in Oracle Machine Learning Describe administering Oracle Machine Learning
Thema 2	Describe the components and features of OML Create a new project and workspace in Oracle Machine Learning
Thema 3	Creating SQL Scripts and Running SQL Commands in Oracle Machine Learning Introduction to Oracle Machine Learning (OML) and Oracle Autonomous Cloud Platform
Thema 4	Describe jobs in Oracle Machine Learning Administering Oracle Machine Learning
Thema 5	Describe personal, shared, and example templates Explain the workflow for managing Oracle Machine Learning
Thema 6	Manage workspaces and workspace permissions Collaborating Using Templates in Oracle Machine Learning
Thema 7	Access the Oracle Machine Learning Home page in Autonomous Data Warehouse Share a notebook by using Oracle Machine Learning templates
Thema 8	Describe a typical workflow for analyzing data with Oracle Machine Learning Create select forms and check-box forms in Notebooks

NR. 36 You are creating a job that should run a notebook every hour. You want to make sure that the job does not run repeatedly if there are more than five consecutive failures to run the job. Which option should you set while creating the job?

Minimum Failure Allowed

Timeout in Minutes

Maximum Failure Allowed

Maximum Number of Runs

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-jobs.html#GUID-

NR. 37 Which two are required by an administrator while adding a new user to Oracle Machine Learning (OML) Notebooks? (Choose two.)

OML username and password

Wallet information to connect to ADB

Privileges to be provided

User’s name and email ID

Autonomous Database (ADB) name

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/administer-oracle-machine-le Create User: An administrator creates a new user account and user credentials for Oracle Machine Learning in the User Management interface. Note: You must have the administrator role to access the Oracle Machine Learning User Management interface. To create a user account: Select an Autonomous Da-ta Warehouse instance and on the details page click Service Console. On the Service Console click Administration. Click Manage OML Users to open the Oracle Machine Learning User Administration page. Click Create on the Oracle Machine Learning User Administration page. In the Username field, enter a username for the account.
Using the username, the user will log in to an Oracle Ma-chine Learning instance. Enter a name in the First Name field. Enter a name in the Last Name field. In the Email Address field, enter the email ID of the user.
Select the option Generate password and email account details to user. User will be required to reset the password on first sign in. to auto generate a temporary password and send an email with the account credentials to the user. If you select this option, you need not enter values in the Password and Confirm Password fields; the fields are grayed out. In the Password field, enter a password for the user, if you choose to create a password for the user.This option is disabled if you select the Generate password… option to auto generate a temporary password for the user. In the Confirm Password field, enter a password to confirm the value that you entered in the Password field.By doing so, you create the password for the user. The user can change the password when first logging in. Click Create. This creates a new database user and grants the required privileges to use Oracle Machine Learning.

NR. 38 Which two templates are supported while saving a notebook? (Choose two.)

Persönlich

Öffentlich

Example

Shared

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/notebooks-templates.html

NR. 39 Which three types of permissions can be granted to a user to callaborate and access a workspace in Oracle Machine Learning Notebooks?

Guest

Verwalter

Betrachter

Manager

Entwickler

* The three types of permissions that can be granted to a user to collaborate and access a workspace in Oracle Machine Learning Notebooks are Viewer, Manager, and Developer1.
* Viewer is a user role that allows users to view notebooks but not run or modify them1.
* Manager is a user role that allows users to perform all the tasks of a Developer as well as manage other users’ workspaces and permissions1.
* Developer is a user role that allows users to create and run notebooks, run SQL statements, create SQL scripts, run Python scripts, create jobs to schedule and run notebooks, use example template notebooks, create and run AutoML experiments, and deploy models1.

NR. 40 You have created a notebook and want to run the notebook on a periodic schedule. How should you achieve this?

You can create a job and schedule it to run a specific notebook.

You cannot run the notebook on the scheduled time.

You need to contact the database administrator to configure the notebook to run at a particular time.

You have to login as the admin user and schedule a job to run the notebook.

Erläuterung
Jobs allow you to schedule the running of notebooks. In the Jobs page, you can create jobs, duplicate jobs, start and stop jobs, delete jobs, and monitor job status by viewing job logs, which are read-only notebooks.
About Jobs. The Jobs page lists all the jobs created, along with the job name, notebook, owner of the job, last start date, next run date, status, and schedule. Create Jobs to Schedule Notebooks You can create jobs to schedule your notebook with preferred scheduling set-tings. View Job Logs You can view the historical logs of any particular job in the Job Log interface. About Jobs The Jobs page lists all the jobs created, along with the job name, notebook, owner of the job, last start date, next run date, status, and schedule.

NR. 41 Which three types of templates are available in Oracle Machine Learning Notebooks? (Choose three.)

Shared templates

Example templates

Personal templates

Public templates

Custom templates

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/use-library-collaborate-users

NO.42 Which option would you use to load data from Object Storage into an Oracle Autonomous Database?

SQL*Loader

DBMS_Cloud package

Oracle SQL Developer Web

Expdp

Erläuterung
About Data Loading: Autonomous Database provides the following loading options: You can load data using Oracle Database Actions. You can load data using Oracle Database tools and Oracle or other 3rd party data integration tools. On transaction processing systems you traditionally ingest data through routine transactions or with DML operations. In general you load data from files local to your client computer or from files stored in a cloud-based object store. To load data from files in the cloud, use either Oracle Database Actions or use the Autonomous Database PL/SQL package DBMS_CLOUD to load files from the cloud. For the fastest data loading experience Oracle recommends uploading the source files to a cloud-based object store, such as Oracle Cloud Infrastructure Object Storage, before loading the data into your database. Oracle provides support for loading files that are located locally in your data center, but when using this method of data loading you should factor in the transmission speeds across the Internet which may be significantly slower. For more information on Oracle Cloud Infrastructure Object Storage, see Putting Data into Object Storage and Overview of Object Storage. Note: If you are not using ADMIN user, ensure the user has the necessary privileges for the operations the user needs to perform. See Manage User Privileges on Autonomous Database – Connecting with a Client Tool for more information.

NO.43 Which category of machine learning algorithms does One-Class SVM fall under?

Clustering

Anomaly Detection

Regression

Classification

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/oracle-machine-learning-sql-guid

NR. 44 Which statement is FALSE about OML Notebooks?

An existing database user cannot be added as an OML user using the User Management Interface.

You must have the Administrator role to access the OML User Management Interface.

You must have the Administrator role to access the compute resources page.

The administrator is not authorized to run notebooks.

* A false statement about OML Notebooks is that an existing database user cannot be added as an OML user using the User Management Interface2.
* An existing database user can be added as an OML user using the User Management Interface by entering the existing database username and password in the Create User dialog box. This will enable the existing database user to access OML Notebooks without creating a new schema2.

NR. 45 Examine the command: %script SET SQLFORMAT ANSICONSOLE What is the output of a query if this SQLFORMAT is set?

It formats the output columns to return ANSI characters.

It formats and resizes the output columns to the width of the data to save space.

It formats the output columns to Add ANSI characters as the delimiter string.

It formats output columns with fixed-width columns with data enclosed in double quotation marks.

Erläuterung
https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/omlug/output-formats-supported-set-sq

NR. 46 Which output formats are supported by the SET SQLFORMAT command? (Choose three.)

TXT

HTML
(Richtig)

JSON

CSV

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/output-formats-supported-set

NR. 47 A user with Developer permission is trying to create a job on an existing notebook that is shared. However, the user is unable to do so. What is the reason?

The specified job already exists.

The notebook contains code with syntax errors, which need to be corrected first.

The user requires the Create Job role.

A developer cannot create jobs for notebooks that are shared.

* The reason why a user with Developer permission is unable to create a job on an existing notebook that is shared is that the user requires the Create Job role1.
* The Create Job role is a database role that grants the privilege to create and manage jobs on Oracle Machine Learning Notebooks. This role is not granted by default to any user, including the ADMIN user. An administrator needs to explicitly grant this role to users who need to create jobs1

NR. 48 How can you share a notebook with multiple developers for a collaborative effort with note-book editing?

You can share notebooks if you have Viewer permissions.

Notebooks cannot be shared for collaborating with other users.

You can share notebooks if you have Developer permissions.

You create different notebooks, edit separately, and merge later.

Erläuterung
You can also collaborate by exporting your notebook as a JSON or JavaScript Object Notation file. This exported file can be imported into the same or different environment. To export a notebook as a JSON file, open the notebook in the notebook editor, click on the Export icon. A Save As dialog will open where you can specify the name of the JSON file and location on your system.

NR. 49 Which notebook technology is used for Oracle Machine Learning in Oracle Autonomous Database?

Polynote

Zeppelin Notebook

Google Colab

Jupyter-Notebook

Erläuterung
Oracle Machine Learning Notebooks is an Apache Zeppelin-based collaborative web-based inter-face that provides a development environment to create machine learning notebooks where you can perform data exploration and visualizations, data preparation and machine learning.
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-oracle-machine-le

NO.50 Which two components support in-database automatic machine learning (AutoML) functionality?

OML AutoML UI

Oracle Data Miner

OML4Py

OML Services

OML4SQL

OML4R

Erläuterung
https://blogs.oracle.com/machinelearning/post/introducing-oml-automl-user-interface
https://www.oracle.com/a/tech/docs/technical-resources/oml-technical-brief.pdf

NR. 51 An OML AutoML UI Experiment is a work unit that minimally contains the definition of which three options?
(Wählen Sie drei aus.)

Prediction Target

Data Source

Parameters

Prediction Type

Algorithm

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-automl-ui/amlui/create-experiment.html

NR. 52 Two users at different locations are collaborating on a project by editing the same notebook. Which type of notebook should they use for collaboration?

Example notebook

Shared Notebook

Public Notebook

Personal Notebook

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/use-library-collaborate-users Use Templates to Collaborate with Users In the Oracle Machine Learning Templates UI, you can collaborate with other users by sharing your work, publishing your work as reports, and by creating notebooks from tem-plates. You can store your notebooks as templates, share notebooks, and provide sample templates to other users. Note: You can also collaborate with other Oracle Machine Learning Notebook users by providing access to your workspace. The authenticated user can then access the projects in your workspace, and access your notebooks. The access level depends on the permission type granted – Manager, Developer, or Viewer.
For more information about collaboration among users, see
unre-solvable-reference.html#GUID-7079D42F-9308-4BEF-B2F2-E74E49A22A87 Use the Personal Templates Personal Templates lists the notebook templates that you have created. Use the Shared Templates In the Shared Templates, you can share notebook templates with all authenticated users the notebook templates you create from existing notebooks available in Templates. Use the Example Templates The Example Templates page lists the pre-populated Oracle Machine Learning notebook templates. You can view and use these templates to create your notebooks.

NR. 53 Which feature of Oracle Machine Learning Notebooks should you use for data analysis, da-ta discovery, data visualization, and collaboration on Oracle Autonomous Database?

Projekt

Job

Notebook

Arbeitsbereich

Erläuterung
https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/create-notebooks-oml.html#GUID-0F489564

NR. 54 When managing Machine Learning models using the OML AutoML UI, what are the three actions that can be performed on Oracle Machine Learning (OML) models from within OML AutoML UI? (Choose three.)

Create a notebook with auto-generated OML4Py code from an OML in-database mod-el to allow for further model tweaking and batch scoring.

Deploy an OML in-database model to a REST endpoint.

Review the model statistics associated with the experiment of an ONNX-format (Open Neural Networks Exchange) model.

Review the model statistics associated with the experiment of an OML in-database model.

Review the model statistics associated with the experiment of an ONNX-format image classification model.

Erläuterung
When managing machine learning models using the OML AutoML UI, three actions that can be performed on Oracle Machine Learning (OML) models from within OML AutoML UI are:
* Create a notebook with auto-generated OML4Py code from an OML in-database model to allow for further model tweaking and batch scoring. This feature enables users to export the selected model as a notebook that contains the OML4Py code to reproduce the model building process and perform additional tasks such as model evaluation, scoring, or deployment1.
* Deploy an OML in-database model to a REST endpoint. This feature enables users to deploy the selected model as a RESTful web service that can be accessed by external applications or tools for real-time scoring or predictions2.
* Review the model statistics associated with the experiment of an OML in-database model. This feature
* enables users to view the details of the model such as the algorithm name, hyperparameters, performance metrics, feature importance, and confusion matrix3.

NR. 55 Which three data sources can be immediately used for model building in Oracle Machine Learning? (Choose three.)

CSV files

Oracle Database tables

Oracle Database views

JSON files

Oracle Database External tables

Erläuterung
The three data sources that can be immediately used for model building in Oracle Machine Learning are:
Oracle Database tables: Oracle Machine Learning can directly access and use data from tables within an Oracle Database for model building. This allows for efficient utilization of the database’s structured data for machine learning tasks. Oracle Database views: Similar to tables, Oracle Machine Learning can also utilize data from database views. Views provide a virtual representation of the data, allowing users to access and analyze specific subsets or transformations of the underlying tables. CSV files: Oracle Machine Learning supports the use of CSV (Comma-Separated Values) files as a data source for model building. CSV files provide a simple and widely-used format for storing tabular data, making it easy to import and use within Oracle Machine Learning. Therefore, the correct options are: Oracle Database tables Oracle Database views CSV files

NO.56 What is the proper workflow for analyzing data in Oracle Machine Learning?

Build the model, prepare the data, evaluate the model, and deploy the model.

Get predictions from the model, prepare the data, build the model, and deploy the model.

Prepare the data, build the model, evaluate the model, and deploy the model.

Evaluate the model, prepare the data, build the model, and deploy the model.

Erläuterung
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/process-overview.html#GUID-A6 Process Overview: The lifecycle of a machine learning project is divided into six phases. The process begins by defining a business problem and restating the business problem in terms of a machine learning objective.
The end goal of a machine learning process is to produce accurate results for solving your business problem.
Workflow: The machine learning process workflow illustration is based on the CRISP-DM method-ology.
Each stage in the workflow is illustrated with points that summarize the key tasks. The CRISP-DM methodology is the most commonly used methodology for machine learning. The following are the phases of the machine learning process: Define business goals Understand data Pre-pare data Develop models Evaluate Deploy

NR. 57 Which type of machine learning algorithm is used to deal with noise in incoming data?

Classification

Regression

Dimensionality Reduction

Clustering

Erläuterung
https://blogs.oracle.com/machinelearning/post/using-svd-for-dimensionality-reduction

NR. 58 For which two types of notebooks can you schedule a job? (Choose two.)

Notebooks under Personal templates

Notebooks owned by you

Notebooks shared with you

Notebooks under Shared templates

Erläuterung
About Workspace Permission Types: Oracle Machine Learning allows three types of permissions. Depending on the permission type, you can allow the user to view or perform different tasks in your workspace, projects, and notebooks. The three types of permissions are listed in the following table along with the actions that are allowed. Permission Types || Actions based on permission > Manager: * Project: Create, update, delete. * Workspace: View only. * Notebooks: Create, update, run, delete, and schedule jobs. > Developer: * Project:
View only. * Workspace: View only. * Notebooks: Cre-ate, update, run, and delete notebooks that a developer creates only. * Jobs: View and run jobs of shared notebooks only. A developer cannot create jobs for notebooks that are shared. > Viewer: * Project: View only. * Workspace: View only. * Notebooks: View only. * Jobs: View jobs and job runs of shared notebooks only.

Laden …